Our abstractive summarisation model is tuned to understand and describe the core idea of a news article or the essence of business, economic, crime or political events. The technology that we use can be applied to different domains too by simply inputting sample data. The process is optimised by a fact-checking algorithm as a step before delivering the final summary to the client.

It is also called opinion mining or emotion AI, which tells you how people feel about a certain topic, be it a person, brand, product or stock, as communicated independently of potentially misleading survey questions. Our multilingual sentiment analysis solution helps you understand attitudes expressed in-text to inform your decisions.

It shows the leading topics from different sources of news articles for the day. Clients can quickly decide whether to invest additional resources in a given topic, according to the readers’ interactions with them. Document collection is clustered into groups with a similar topic which is described by a set of keywords. Each document is annotated with a quantity of Facebook comments, shares and reactions (engagement), so that engagement can be easily assigned to a particular topic. Topic modelling, a key part of the whole analysis, is based on a statistical approach and is language-agnostic.

Our Share of Voice can show you every single mention of your brand. We focus only on the relevant coverage of the predefined keywords, so you can monitor not only your brand but conduct competitor analysis or gain any kind of information you need. This solution can be additionally enriched with automated sentiment analysis for greater precision.

Our automated reports save you time and effort. This solution provides you with an automated quantitative and qualitative analysis of the data you want to gain knowledge from.